ARTICLE

Interactively Comparing Superpixel Algorithms using d3.js and NVD3

This article presents visualizations of the qualitative and quantitative results from the superpixel benchmark published in CVIU. Based on NVD3 and Unite Gallery, the visualizations allow to interactively compare different superpixel algorithms in the browser.

After getting our superpixel benchmark published in CVIU [1], I also wanted to make the results more accessible. To this end, I intended to provide interactive plots of the newly introduced metrics — namely Average Miss Rate (AMR), Average Undersegmentation Error (AUE) and Average Unexplained Variation (AUV) — as well as a gallery of qualitative results. For interactive plots, I decided to use NVD3 (as I did for the results from my bachelor thesis, too). To make the qualitative results available, I chose Unite Gallery.

Both the interactive plots and the gallery can be found online; the source code is available on GitHub:

ABOUTTHEAUTHOR

In September, I was honored to receive the MINT-Award IT 2018, sponsored by ZF and audimax, for my master thesis on weakly-supervised shape completion. For CVPR 2019, however, I am working on a different topic: adversarial robustness and generalization of deep neural networks.
18thOCTOBER2018 , David Stutz

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